Research background
Globalization has made the world more interconnected, reducing the distance between nations and facilitating easier business transactions, access to information, and modern education Vietnam's accession to the World Trade Organization (WTO) has opened up numerous opportunities for expanding international relationships, allowing exporters to reach broader markets and providing citizens with diverse goods and educational opportunities However, this also presents challenges such as increased competition and the necessity for continual knowledge updates In the educational sector, it is crucial to train a workforce that can effectively collaborate with foreign partners and adapt to ongoing global changes Consequently, many Vietnamese universities are focusing on enhancing the quality of their training programs.
Numerous studies worldwide aim to enhance the effectiveness of student learning and the quality of education A significant trend in this research emphasizes the importance of learning motivation and the overall quality of life for students This focus is driven by the understanding that motivation, study behaviors, and students' quality of life significantly influence the quality of training and the perceived outcomes during their educational journey (Cole et al 2004; Rowold 2007, cited in Tho et al 2009).
Learning motivation is crucial for success, as motivated individuals are more likely to put in the effort needed to complete tasks and achieve their goals In contrast, those lacking motivation may not only fail to try but may also engage in behaviors that undermine their potential outcomes.
Psychological hardiness enables individuals to effectively manage life's pressures and unexpected challenges, transforming potential obstacles into opportunities for personal growth (Maddi, 1999a; Kobasa & Puccetti, 1983, as cited in Tho et al., 2009).
The quality of life for students is influenced by two main trends: the first examines the relationship between students' quality of life and various impacting factors, while the second emphasizes the measurement of students' quality of life (Sirgy et al 2007, cited in Tho et al 2009).
Our universities are focusing on enhancing training quality to meet labor market demands In Vietnam, research on student psychology, particularly concerning quality of life and factors like learning motivation and psychological hardiness, is limited Such studies are essential for universities to gain insights into student psychology, which can inform strategies to boost learning and training effectiveness Therefore, conducting research at Lac Hong University on the impact of learning motivation and psychological hardiness on students' quality of life is crucial This study aims to provide evidence of the relationship between these factors and to develop appropriate plans to improve students' quality of life and learning effectiveness Additionally, the research will explore differences in the impact of learning motivation and psychological hardiness on quality of life between economics and technical student groups.
Research objective
This research aims to investigate how learning motivation and psychological hardiness affect the quality of life of economics and technical students at Lac Hong University Specifically, it seeks to address key questions regarding these factors' influence on students' overall well-being.
Question 1: Do learning motivation and psychological hardiness impact on student’s quality of life?
Question 2: Are there differences of the impact of learning motivation and psychological hardiness on student’s quality of life if compared the economics student group with the technical student group?
This research highlights the significance of learning motivation, psychological hardiness, and students' quality of life in enhancing educational outcomes By understanding these factors, universities can develop strategies to boost student learning effectiveness and overall training quality Students will discover how these elements contribute to improved learning attitudes, increased motivation, and better psychological resilience, ultimately leading to a higher quality of life and enhanced academic performance.
Research scope and research design
This research is conducted at Dong Nai province The research object is technical students and economics students of Lac Hong university
The process research will include two main steps: the pilot research and the main research, the analytic unit is student
The pilot research will be qualitative by making deeply interview with
7 students in order to check the content and the meaning of words using in the measurement scales
This research will employ a quantitative approach involving 328 economics and technical students, complemented by qualitative interviews The primary aim is to evaluate the measurement model, research model, and associated hypotheses.
The reliability of the measurement scales will be assessed using the Cronbach's alpha ratio, followed by Exploratory Factor Analysis (EFA) to refine these scales Ultimately, the hypotheses will be evaluated through multi-linear regression analysis.
LITERATURE REVIEW AND RESEARCH MODEL
Concepts
The quality of life is a multi-direction definition and complication that is measured by many different ways (Vaez et al 2004)
The quality of student life encompasses various subjective experiences such as satisfaction, happiness, and optimism during adolescence (Nussbaum and Sen, 1993; Staats et al., 1995) It is influenced by health behaviors, emotional well-being, and sociocultural and political factors (Disch et al., 1997) Additionally, students' current financial situations and future career aspirations play a significant role in shaping their perceptions of how a college degree may impact their quality of life (Sax, 1996) Ultimately, a student's quality of life can be defined as their level of satisfaction throughout their university experience, which is assessed based on factors such as relationships with teachers, access to learning resources, university support, friendships, and extracurricular activities (Sirgy et al., 2007, cited in Tho et al., 2009).
Research on students' quality of life can be categorized into two main trends: the first trend focuses on the various factors that influence students' quality of life, while the second trend emphasizes the methods for measuring this quality of life (Sirgy et al 2007, cited in Tho et al 2009).
Research indicates various factors influencing students' quality of life Cha (2003) highlights a positive correlation between life satisfaction and personality traits such as optimism and self-respect Vaez et al (2004) establish a link between health status and students' quality of life In Vietnam, Tho et al (2009) studied economics students from public and private universities, revealing that learning motivation does not enhance quality of life but is positively associated with it in public universities, while negatively correlated in private ones The study also found that psychological hardiness positively affects both quality of life and learning motivation, with a greater impact in private universities Additionally, learning value is positively related to psychological hardiness, learning motivation, and quality of life, although its influence on psychological hardiness is less significant in public universities The effect of learning value on learning motivation remains consistent across both types of institutions, and the differences in its impact on students' quality of life between public and private universities are not significant.
This study will examine the impact of learning motivation and psychological hardiness on student’s quality of life
Motivation is a complex and subjective concept that is challenging to measure or define clearly While one can observe behaviors to infer an individual's motivation, certainty remains elusive Ultimately, motivation is a deeply personal experience that varies from person to person.
Motivation is the driving force behind our thoughts and actions, serving as a crucial element in striving to achieve goals (Lumsden, 1994) For instance, many students are highly motivated by the desire to avoid failure, while others may lose their motivation based on their personal values (Mowl, 1996).
Motivation is defined as the driving force behind human actions, sustaining activities and aiding in task completion (Pintrich, 2003, cited in Tho et al., 2009) Learning motivation, as described by Noe (1986, cited in Tho et al., 2009), refers to the desire to engage with and absorb the material of a subject or training program.
According to Fallows and Ahmet (1999), several factors influence a student's motivation to learn, including the desire to please teachers, the perceived need to grasp the material, and the individual's interest in the subject Additionally, personal values and beliefs, attitudes toward the learning materials, academic and career goals, and anticipated rewards also play significant roles in shaping a learner's engagement and commitment to their education.
According to Entwistle (1998), motivation for valuing learning can be categorized into three main types: extrinsic motivation, which involves the desire to complete a course for anticipated rewards; intrinsic motivation, stemming from a genuine interest in the subject matter; and achievement motivation, characterized by the aspiration to excel and outperform peers.
Psychological hardiness is a latent variable that encompasses three key components: commitment, control, and challenge (Canava et al 2001, cited in Tho et al 2009) Commitment involves dedicating one's full mental and physical energy to tackle challenges, while control reflects an active approach to managing unexpected events Challenge embodies a positive outlook on life's changes, viewing them as opportunities for growth rather than threats (Kobasa et al 1982, cited in Tho et al 2009) To effectively navigate the stressful situations and problems that life presents, individuals must cultivate the characteristics of hardiness.
In learning situation, researchers find out that learning is one of the most stressful activities to university students (Cole et al 2004; Furr et al
Psychological hardiness is crucial for university students, as it encompasses commitment, control, and challenge, enabling them to effectively manage both academic responsibilities and personal challenges According to research by Britt et al (2001) and Kobasa et al (1982), students who exhibit psychological hardiness are better equipped to navigate the stresses of exams, projects, and readings, while also balancing financial concerns, part-time jobs, and social activities This resilience is essential for overcoming stressful events and problems throughout their university experience (Tho et al 2009).
Psychological hardiness is a crucial factor in enhancing work effectiveness and overall health during stressful events, as noted by Maddi (1999a) in Tho et al (2009) It enables individuals to manage life's pressures and transform challenges into opportunities for personal development (Kobasa & Puccetti, 1983, cited in Tho et al 2009) Ultimately, psychological hardiness empowers people to tackle stressful situations, turning them into manageable issues and valuable growth opportunities, thereby improving both their quality of life and work performance (Wiebe & McCallum).
1986, cited in Tho et al 2009).
METHODOLOGY
Research process
The research process comprised two distinct phases: the pilot research, which employed qualitative methods, and the main research, which utilized quantitative methods The unit of analysis focused on students, specifically those studying technical and economics disciplines at Lac Hong University.
THE MAIN RESEARCH USING THE MAIN
Reliability analysis, Exploratory Factor Analysis (EFA), Linear regression analysis
(Student’s quality of life, Learning motivation, psychological hardiness,
THE PILOT RESEARCH USING THE INNITIAL
In August 2010, a pilot research study was conducted utilizing qualitative methods, which involved in-depth interviews with seven students This approach aimed to explore and analyze the content and meanings of the words used in measurement scales.
The main research, following a pilot study, utilized a quantitative method involving direct interviews with 328 students to validate the measurement model, research model, and hypotheses The collected data underwent reliability analysis, eliminating items with low total correlation (below 0.30) and those with a Cronbach's alpha below 0.60, along with Exploratory Factor Analysis (EFA) to ensure robust findings.
(Deleted items with low loading factor < 0.50) The hypotheses were tested by the multi-linear regression with Enter method.
The measurement scales
Research has established definitions and measurement scales for students' quality of life, learning motivation, and psychological hardiness across various countries Notable studies include those by Sirgy et al (2007) and Cole et al (2004), which have been cited in subsequent research, highlighting the validity of these measurement tools in assessing students' overall well-being and resilience.
This research utilizes measurement scales inherited from Tho et al (2009) and applies them within the current context of Lac Hong University in Vietnam The scales have been translated into English to ensure clarity and accuracy in this study.
Vietnamese measurement scales presented in Tho et al (2009) The measurement scales of this research were measured basing on the Likert 5 point, with 1: fully – againsted; 5: fully-agreed
3.2.1 The student’s quality of life measurement
This value was measured basing on the measure of student’s quality of life of Sirgy et al (2007) (cited in Tho et al 2009) It included 6 observed variables: coded from Q1 to Q6
Q1: I’m very pleased with the teaching of teachers at this university Q2: I’m very pleased with the material facilities and equipments at this university
Q3: I’m very pleased with the treatment to students at this university Q4: I’m very pleased with the extra – activities of the course at this university
Q5: I’m very pleased with relationship with my classmates when study at this university
Q6: In generally, my learning quality of life is very high at this university
This measure was based on the measure of learning motivation of (Cole et al 2004, cited in Tho et al 2009) It included 5 observed variables, coded from M1 to M5
M1: I try my best to invest into my learning
M2: I spend most of time on this subject
M3: Investment into this subject is my first priority
M4: I use all of my energy to learn this subject
M5: In generally, my learning motivation with this subject is very high
The measure of psychological hardiness, as established by Cole et al (2004) and referenced in Tho et al (2009), consists of seven observed variables, labeled H1 to H7 These variables reflect students' capacity to endure and manage stress throughout their university experience.
H1: Despite all changes, I always commit to complete my course at university
H2: When necessary, I’m willing to work hard in order to reach learning goals
H3: When I have problems with my learning, I can always solve them H4: I can always control all difficulties happening to me during the course
The main research
Chapter 3 will provide methodology that uses to examine the measurement scales of concepts and verify research model and hypotheses given
The research process comprised two distinct phases: a pilot study and a main study The pilot research employed qualitative methods, while the main research utilized quantitative methods The focus of the analysis centered on students, specifically those studying technical and economics disciplines at Lac Hong University.
THE MAIN RESEARCH USING THE MAIN
Reliability analysis, Exploratory Factor Analysis (EFA), Linear regression analysis
(Student’s quality of life, Learning motivation, psychological hardiness,
THE PILOT RESEARCH USING THE INNITIAL
RESEARCH RESULT AND FINDING DISSCUSSION
Descriptive statistics of sanple
A total of 350 students participated in the questionnaire survey, resulting in a 9.4 percent missing rate and yielding 328 usable responses Consequently, the analysis presented in this chapter is based on the complete sample of 328 responses, achieving a 100 percent usable response rate for the research interview.
This research was conducted using two groups of students – economics students and technical students The number of responses about each group was provided in Table 4.1
Table 4.1: Learning group of respondents
Table 4.1 showed that there were 328 respondents, with 54.9 percent of the respondents were economics students; 45.1 percent of the respondents were technical students
The respondents also were divided into learning brand, gender and age They were presented in the following in table 4.2, 4.3 and 4.4
Table 4.2: Learning brand of respondents
Learning brand Frequency Percent Cumulative Percent
Table 4.2 showed that 89.6 percent of respondents were full-time students, and 10.4 percent of them were non-full time students
Gender Frequency Percent Cumulative Percent
In the table 4.3, 328 respondents were devided by gender, including 70.7 percent of the male respondents and 29.3 percent of the female respondents
Age Frequency Percent Cumulative Percent
Table 4.4 reveals the age distribution of respondents, with 67.4% aged 18 to 22 years, 28.7% between 23 and 27 years, 3.7% from 28 to 35 years, and only 0.3% over 35 years old.
Descriptive statistics for each measurement item were presented in Table 4.5, including minimum, maximum, means and standard deviations
N Minimum Maximum Mean Std Deviation
The construct measurement scale
This research employed Cronbach’s alpha and exploratory factor analysis to evaluate the reliability and validity of measurement scales Items with low item-total correlations (below 0.3) were removed using Cronbach’s alpha, with a minimum acceptable alpha value set at 0.6, as suggested by Tho et al (2009).
Cronbach’s alpha results of each measurement
Table 4.6: Cronbach’s alpha of student’s quality of life measurement
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Table 4.7: Cronbach’s alpha of learning motivation measurement
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Table 4.8: Cronbach’s alpha of psychological hardiness measurement
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The measurement scales for students' quality of life, learning motivation, and psychological hardiness demonstrated a Cronbach's Alpha of 0.872, indicating strong reliability All items, except for H5, exhibited Corrected Item-Total Correlations exceeding 0.3, leading to the elimination of item H5 Consequently, the remaining items met the necessary criteria for inclusion in Exploratory Factor Analysis.
Exploratory Factor Analysis (EFA) was conducted to refine the measurement scale by removing unsuitable items, adhering to specific criteria The analysis required a Kaiser-Meyer-Olkin (KMO) value of at least 0.5, with the final KMO recorded at 0.870 Items with factor loadings below 0.5 and eigenvalues under 1 were eliminated, ensuring that the total variance extracted met the threshold of 50%, which was achieved at 61.356% Utilizing principal axis factoring and promax rotation, the analysis identified three distinct factors, demonstrating that these factors account for a significant portion of data variability All retained items exhibited factor loadings greater than 0.5, confirming the validity of the EFA results.
Table 4.9: The Exploratory Factor Analysis (EFA) result
Extraction Method: Principal Axis Factoring
Rotation Method: Promax with Kaiser Normalization
The study assessed the construct measurement scale, with Table 4.10 displaying the final instrument used after the removal of item H5 The following section will concentrate on testing the hypotheses based on the research model outlined in Chapter 2.
Table 4.10: The final construct of measurement scale
I’m very pleased with the teaching of teachers at this university Q1
I’m very pleased with the material facilities and equipments at this university Q2
I’m very pleased with the treatment to students at this university Q3
I’m very pleased with the extra – activities of the course at this university Q4
I’m very pleased with relationship with my classmates when study at this university Q5
In generally, my learning quality of life is very high at this university Q6
I try my best to invest into my learning M1
I spend most of time on this subject M2
Investment into this subject is my first priority M3
I use all of my energy to learn this subject M4
In generally, my learning motivation with this subject is very high M5
Despite all changes, I always commit to complete my course at university H1
When necessary, I’m willing to work hard in order to reach learning goals H2
When I have problems with my learning, I can always solve them H3
I can awlays control all difficulties happening to me during the course H4
I can always deal with unexpected problems during the course H6
In generally, I have high ability to bear pressures during the course H7
The hypotheses assessment
Afer EFA (Exploratory Factor Analysis), there were 3 factors which were accepted in order to assess research model The factor value was the mean of observative items of that factor
To evaluate the hypotheses, a Pearson correlation analysis was initially conducted to determine the suitability of the factors for inclusion in the regression model Subsequently, a multi-linear regression analysis was performed to test the hypotheses H1 and H2, utilizing data collected from 328 students.
To test the hypotheses H3, H4, H5, and H6, the data was segmented into two groups: economics students and technical students A multi-linear regression analysis was performed on both groups to compare the results and identify any differences in the impact of the presented variables.
The correlation analysis was to test the linear relationships between the dependent variables and independent variables
The correlation matrix revealed the relationships among the study variables, with correlation coefficients ranging from 0.386 to 0.527 Additionally, the means and standard deviations of these variables were provided in the accompanying table.
Based on the results of the multi-linear regression analysis on data of
The analysis involved 328 responses, revealing an adjusted R square of 0.303, with a significance level of 0.000, well below the 0.05 threshold (Appendix 2) For group 1, consisting of economics students, the adjusted R square was notably higher at 0.566, also with a significance level of 0.000 (Appendix 3) In contrast, group 2, comprising technical students, showed an adjusted R square of 0.132, with a significance level of 0.000 (Appendix 4) These results indicate a strong basis for rejecting the null hypothesis of regression coefficients being equal to 0, confirming that the multi-linear regression model is appropriate and applicable to the population data Consequently, we proceeded to evaluate hypotheses H1 to H6.
Table 4.11: The results of correlation analysis
** Correlation is significant at the 0.01 level (2-tailed)
Table 4.12: The results of multi-linear regression analysis on data of 328 responses
Collinearity Statistics Model B Std Error Beta t Sig Tolerance VIF
From Table 4.12, it showed that there was no multicollinearity between the indenpdent variables ( all VIF values are less than 10) (Trong & Ngoc
Hypothesis 1: Learning motivation is positively related to student’s quality of life
This hypothesis suggested that students would tend to be satisfied with their learning at university if they had a positive learning motivation
The multi-linear regression results indicated a significant positive relationship between learning motivation and students' quality of life, with a standardized coefficient beta of β = 0.191 (t = 3.723, sig = 0.000) This confirms that higher learning motivation positively influences students' quality of life, thus supporting hypothesis 1.
Hypothesis 2: Psychological hardiness is positively related to student’s quality of life
Hypothesis 2 supposed that students with a high psychological hardiness would be more satisfied during their course at university or getting a higher quality of life
The multi-linear regression analysis results in Table 4.12 showed that the standardized coefficient beta between psychological hardiness and student’s quality of life was positive and significant (β =0.443, t =8.629, sig
=0.000) demonstrating that hypothesis 2 was accepted by the data
Research indicates a positive correlation between psychological hardiness and students' quality of life When students develop the ability to manage challenges and unexpected events throughout their educational journey, they experience greater satisfaction and an enhanced quality of life Higher levels of psychological hardiness are associated with improved well-being among university students Further discussion on this topic will be provided in the next section.
Following, the content focussed on testing hypothesis 3, 4, 5 and 6 The data was divided into two groups, group 1 stands for the economics student group, group 2 stands for the technical student group
Table 4.13: The multi-linear regression analysis on data of group 1
Collinearity Statistics Model B Std Error Beta t Sig Tolerance VIF
Psychological hardiness 430 077 417 5.588 000 434 2.302 a Dependent Variable: Student’s quality of life
From Table 4.13, there was no multicollinearity between the independent variables ( all VIF values are less than 10)
Table 4.14: The multi-linear regression analysis on data of group 2
Collinearity Statistics Model B Std Error Beta t Sig Tolerance VIF
Psychological hardiness 413 095 341 4.351 000 963 1.039 a Dependent Variable: Student’s quality of life
From Table 4.14, there was no multicollinearity between the indenpdent variables ( all VIF values are less than 10)
Hypothesis 3: Learning motivation is positively related to student’s quality of life in the economics student group
Hypothesis 3 supposed that learning motivation is positively related to student’s quality of life in the economics student group
The multi-linear regression analysis for economics students revealed a significant positive relationship between learning motivation and students' quality of life, with a standardized coefficient beta of 0.390 (t = 5.220, sig = 0.000) This indicates that higher learning motivation is associated with an improved quality of life among economics students.
Hypothesis 4: Learning motivation is positively related to student’s quality of life in the technical student group
The multi-linear regression analysis for technical students revealed a positive standardized coefficient beta of 0.112 between learning motivation and quality of life; however, this result was not significant, as the p-value of 0.156 exceeded the 0.05 threshold Consequently, it can be concluded that there is no linear relationship between learning motivation and quality of life among technical students.
Hypothesis 5: Psychological hardiness is positively related to student’s quality of life in the economics student group
The multi-linear regression analysis results for group 1 (economics students) indicated a significant positive relationship between psychological hardiness and quality of life, with a standardized coefficient beta of 0.417 (t = 5.588, sig = 0.000) This suggests that higher levels of psychological hardiness among economics students are associated with an improved quality of life.
Hypothesis 6: Psychological hardiness is positively related to student’s quality of life in the technical student group
The multi-linear regression analysis of technical students revealed a significant positive relationship between psychological hardiness and quality of life, with a standardized coefficient beta of 0.341 (t = 4.351, p < 0.001) This indicates that higher levels of psychological hardiness are associated with an improved quality of life among technical students.
After regression analysis, we had conclusion about the hypotheses test of the research model:
Table 4.15: Conclusion about the hypotheses
H1 Learning motivation is positively related to student’s quality of life Accepted H2 Psychological hardiness is positively related to student’s quality of life Accepted
H3 Learning motivation is positively related to student’s quality of life in the economics student group
H4 Learning motivation is positively related to student’s quality of life in the technical student group
H5 Psychological hardiness is positively related to student’s quality of life in the economics student group
H6 Psychological hardiness is positively related to student’s quality of life in the technical student group
CONCLUSION AND IMPLICATIONS
Concluding remarks
This research examines student psychology through three key definitions: quality of life, learning motivation, and psychological hardiness The measurement scales utilized in the study demonstrated reliability and validity, as confirmed by Cronbach's alpha and Exploratory Factor Analysis (EFA) results.
This research makes a theoretical contribution to verify the construct measurement scales of student’s quality of life and the two presented factors within Lac Hong university context
The research findings indicate that many instruments adapted from studies in developed countries demonstrate reliability and validity in the context of developing markets This study contributes to the theoretical framework by encouraging future research to modify, enhance, and apply these measurement scales specifically within the Vietnamese educational context.
This research aims to explore the relationship between various psychological factors while also providing educational leaders with valuable insights into students' perceptions of learning motivation, psychological hardiness, and quality of life at their university By measuring these factors, leaders can implement targeted strategies to enhance students' learning effectiveness and overall training outcomes.
Implications of the research
This research focuses on exploring the impact of earning motivation, psychological hardiness on student’s quality of life The results of this research suggests following implications for university leaders
The research provides some guidances on psychological strategies from students’s perspective
This research demonstrates a positive correlation between learning motivation and psychological hardiness in relation to students' quality of life Notably, psychological hardiness exerts a greater influence on quality of life than learning motivation Therefore, university leaders should prioritize the development of psychological hardiness to enhance students' overall well-being.
Research at Lac Hong University reveals varying impacts of learning motivation and psychological hardiness on the quality of life of economics and technical students The study indicates that these factors influence students differently based on their fields of study Consequently, university leaders should consider these differences when developing strategies to enhance student support and motivation.
In summary, student’s quality of life is a valuable tool for a university
It is not only a factor that helps students to reach to their goal of learning effectiveness, but aslo helps university to assess their training effectiveness
As Vietnam's economy continues to open up, competition in the market intensifies, leading to an increased demand for skilled labor This surge in demand drives more students to pursue higher education at universities In response, universities are expanding their training programs and seeking innovative ways to enhance training quality Improving training quality not only elevates students' educational experiences but also enhances their overall quality of life To effectively boost students' quality of life, university leaders must focus on key influencing factors This research provides evidence to support initiatives aimed at improving students' quality of life at Lac Hong University, offering a new direction for university leaders to develop strategies that enhance learning effectiveness and training outcomes, ultimately creating a competitive advantage for their institution.
Limitations of the research and further research recommendation
The research has some limitations
This research is confined to the context of Lac Hong University, and results may vary in different educational settings Future studies should explore the effects of learning motivation and psychological hardiness on students' quality of life across diverse educational and training environments to yield more representative findings.
The research primarily targets economics and technical students, suggesting that the findings regarding the influence of the two factors on students' quality of life may vary if the study were to include participants from different academic disciplines.
This research reveals that the factors influencing the quality of life differ significantly between economics and technical students It proposes potential reasons for these varying outcomes, indicating a need for further investigation to clarify these findings.
This research focuses on the influence of learning motivation and psychological hardiness on students' quality of life However, it acknowledges that other factors, such as the value placed on learning, health, and personality traits like optimism and self-respect, may also play a significant role These considerations could serve as valuable directions for future studies.
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A study by Vaez, Kristenson, and Laflamme (2004) examined the perceived quality of life and self-rated health among first-year university students, comparing these factors with those of their working peers, revealing significant differences in well-being Additionally, Wiebe and McCallum (1986) explored the role of health practices and hardiness as mediators in the relationship between stress and illness, highlighting the importance of resilience and proactive health behaviors in managing stress-related health outcomes.
NGHIÊN CỨU VỀ SINH VIÊN KHỐI NGÀNH KINH TẾ VÀ KHỐI NGÀNH KĨ THUẬT
Bài viết này nhằm khảo sát mối quan hệ giữa động cơ học tập, tính kiên định trong học tập và chất lượng sống của sinh viên thuộc khối ngành kinh tế và kỹ thuật Chúng tôi rất mong nhận được ý kiến đóng góp từ bạn về những phát biểu dưới đây Mọi ý kiến của bạn đều có giá trị và sẽ được chúng tôi trân trọng xem xét trong nghiên cứu này Rất mong nhận được sự phản hồi trung thực từ bạn.
Phần I: Vui lũng cho biết mức ủộ ủồng ý của bạn cho cỏc phỏt biểu dưới ủõy khi bạn học tại trường ðại học Lạc Hồng, theo thang ủiểm từ 1 ủến 5 với quy ước sau ủõy:
1: Hoàn toàn phản ủối ðến 5: Hoàn toàn ủồng ý (Chỉ khoanh tròn một số thích hợp cho từng phát biểu)
STT Phỏt biểu Thang ủiểm
1 Tụi cố gắng ủầu tư tối ủa cho việc học 1 2 3 4 5
2 Tôi dành rất nhiều thời gian cho việc học 1 2 3 4 5
3 ðầu tư vào việc học là ưu tiên số một của tôi 1 2 3 4 5
4 Tôi học hết mình trong quá trình học tập 1 2 3 4 5
5 Nhỡn chung, ủộng cơ học tập của tụi rất cao 1 2 3 4 5
6 Dự cú khú khăn gỡ ủi nữa, tụi luụn cam kết hoàn thành việc học của tụi tại trường 1 2 3 4 5
7 Khi cần thiết tụi sẵn sàng làm việc cật lực ủể ủạt mục tiờu học tập 1 2 3 4 5
8 Khi gặp vấn ủề khú khăn trong học tập, tụi luụn cú khả năng giải quyết nú 1 2 3 4 5
9 Tụi luụn kiểm soỏt ủược những khú khăn xảy ra với tụi trong học tập 1 2 3 4 5
10 Tôi luôn thích thú với những thử thách trong học tập 1 2 3 4 5
11 Tụi luụn cú khả năng ủối phú với những khú khăn khụng lường hết trong học tập 1 2 3 4 5
12 Nhỡn chung, khả năng chịu ủựng những ỏp lực trong học tập của tụi rất cao 1 2 3 4 5
13 Tôi rất hài lòng với các giảng viên giảng dạy tôi tại trường này 1 2 3 4 5
14 Tôi rất hài lòng với cơ sở vật chất và trang thiết bị học tập của trường này 1 2 3 4 5
15 Tụi rất hài lũng với cung cỏch ủối xử với sinh viờn của trường này 1 2 3 4 5
16 Tụi rất hài lũng với cỏc hoạt ủộng ngoại khúa khi học tập tại trường này 1 2 3 4 5
17 Tôi rất hài lòng với quan hệ bạn bè cùng lớp khi học tập tại trường này 1 2 3 4 5
18 Nhìn chung, chất lượng sống trong học tập của tôi tại trường này rất cao 1 2 3 4 5
Phần II: Vui lòng cho biết một số thông tin về bản thân:
19 Hệ học: Chính quy dài hạn Khác (văn bằng 2, tại chức,…)
20 Khối ngành học: Khối ngành Kinh tế Khối ngành kĩ thuật
21 Thời gian học: Lớp ngày Lớp ủờm
Std Error of the Estimate
1 554 a 307 303 57920 a Predictors: (Constant), psychological hardiness, learning motivation
Total 157.415 327 a Predictors: (Constant), psychological hardiness, learning motivation b Dependent Variable: Student’s quality of life
Model Summary Model R R Square Adjusted R Square
Std Error of the Estimate
1 756 a 571 566 38359 a Predictors: (Constant), psychological hardiness, learning motivation
Model Sum of Squares Df Mean Square F Sig
Total 60.705 179 a Predictors: (Constant), psychological hardiness, learning motivation b Dependent Variable: Student’s quality of life
Std Error of the Estimate
1 379 a 143 132 72692 a Predictors: (Constant), psychological hardiness, learning motivation
Squares Df Mean Square F Sig
Total 89.444 147 a Predictors: (Constant), psychological hardiness, learning motivation b Dependent Variable: Student’s quality of life